Generalized surface flows for deformable registration and cortical matching

Authors:
I. Eckstein;A. A. Joshi;C.-C. J. Kuo;R. Leahy;M. Desbrun
Affiliations:
Department of Computer Science, University of Southern California;Signal and Image Processing Institute, University of Southern California;Signal and Image Processing Institute, University of Southern California;Signal and Image Processing Institute, University of Southern California;Department of Computer Science, Caltech
Venue:
MICCAI'07 Proceedings of the 10th international conference on Medical image computing and computer-assisted intervention - Volume Part I
Year:
2007

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Abstract

Despite being routinely required in medical applications, deformable surface registration is notoriously difficult due to large intersubject variability and complex geometry of most medical datasets.We present a general and flexible deformable matching framework based on generalized surface flows that efficiently tackles these issues through tailored deformation priors and multiresolution computations. The value of our approach over existing methods is demonstrated for automatic and user-guided cortical registration.